人工知能学会論文誌
Online ISSN : 1346-8030
Print ISSN : 1346-0714
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強連結成分の性質を用いたOWCTYモデル検査アルゴリズムの高速化
川端 聡基小林 史佳上田 和紀
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26 巻 (2011) 2 号 p. 341-346

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Model checking is an exhaustive search method of verification. Automata-based LTL model checking is one of the methods to solve accepting cycle search problems. Model checking is prone to state-space explosion, and we may expect that parallel processing would be a promising approach. However, the optimal sequential algorithm is based on post-order depth-first seach and is difficult to parallelize. Alternative parallel algorithms have been proposed, and OWCTY_reversed is one of them. OWCTY_reversed is known to be a stable and fast algorithm for models that accept some words, but it does not use the characteristics of the automata used in LTL model checking. We propose a new algorithm named SCC-OWCTY that exploits the SCCs (strongly connected components) of property automata. The algorithm removes states that are judged not to form accepting cycles faster than OWCTY_reversed. We experimented and compared the two algorithms using DiVinE, and confirmed improvements both in performance and scalability.

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© 2011 JSAI (The Japanese Society for Artificial Intelligence)
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